ArticleLife (Basel, Switzerland)2022
Identification of Cell Markers and Their Expression Patterns in Skin Based on Single-Cell RNA-Sequencing Profiles.
Article in Life (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 26 citations in OpenAlex.
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- Machine Learning Classification of Time since BNT162b2 COVID-19 Vaccination Based on Array-Measured Antibody Activity.Life (Basel, Switzerland) · 2023Article
- Identification of Genes Associated with the Impairment of Olfactory and Gustatory Functions in COVID-19 via Machine-Learning Methods.Life (Basel, Switzerland) · 2023Article
- Identification of Smoking-Associated Transcriptome Aberration in Blood with Machine Learning Methods.BioMed research international · 2023Article
- Identification of Transcriptome Biomarkers for Severe COVID-19 with Machine Learning Methods.Biomolecules · 2022Article
- Identifying MicroRNA Markers That Predict COVID-19 Severity Using Machine Learning Methods.Life (Basel, Switzerland) · 2022Article
- Identifying COVID-19 Severity-Related SARS-CoV-2 Mutation Using a Machine Learning Method.Life (Basel, Switzerland) · 2022Article
- Identifying anal and cervical tumorigenesis-associated methylation signaling with machine learning methods.Frontiers in oncology · 2022Article
- Characterization of spleen and lymph node cell typesFrontiers in molecular neuroscience · 2022Article
- Identification of COVID-19 severity biomarkers based on feature selection on single-cell RNA-Seq data of CD8Frontiers in genetics · 2022Article
- Identification of Methylation Signatures and Rules for Sarcoma Subtypes by Machine Learning Methods.BioMed research international · 2022Article
- Identifying In Vitro Cultured Human Hepatocytes Markers with Machine Learning Methods Based on Single-Cell RNA-Seq Data.Frontiers in bioengineering and biotechnology · 2022Article
- Detecting Brain Structure-Specific Methylation Signatures and Rules for Alzheimer's Disease.Frontiers in neuroscience · 2022Article
- Identification of COVID-19-Specific Immune Markers Using a Machine Learning Method.Frontiers in molecular biosciences · 2022Article
- Identification of Human Cell Cycle Phase Markers Based on Single-Cell RNA-Seq Data by Using Machine Learning Methods.BioMed research international · 2022Article
- Identification of methylation signatures associated with CAR T cell in B-cell acute lymphoblastic leukemia and non-hodgkin's lymphoma.Frontiers in oncology · 2022Article
- Identification of uveitis-associated functions based on the feature selection analysis of gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment scores.Frontiers in molecular neuroscience · 2022Article
- Identification of protein-protein interaction associated functions based on gene ontology and KEGG pathway.Frontiers in genetics · 2022Article
- Identification of methylation signatures and rules for predicting the severity of SARS-CoV-2 infection with machine learning methods.Frontiers in microbiology · 2022Article
Corrections and comments
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Authors and funding
8 authors at 6 institutions in 1 country.
Funding
Abstract
Atopic dermatitis and psoriasis are members of a family of inflammatory skin disorders. Cellular immune responses in skin tissues contribute to the development of these diseases. However, their underlying immune mechanisms remain to be fully elucidated. We developed a computational pipeline for analyzing the single-cell RNA-sequencing profiles of the Human Cell Atlas skin dataset to investigate the pathological mechanisms of skin diseases. First, we applied the maximum relevance criterion and the Boruta feature selection method to exclude irrelevant gene features from the single-cell gene expression profiles of inflammatory skin disease samples and healthy controls. The retained gene features were ranked by using the Monte Carlo feature selection method on the basis of their importance, and a feature list was compiled. This list was then introduced into the incremental feature selection method that combined the decision tree and random forest algorithms to extract important cell markers and thus build excellent classifiers and decision rules. These cell markers and their expression patterns have been analyzed and validated in recent studies and are potential therapeutic and diagnostic targets for skin diseases because their expression affects the pathogenesis of inflammatory skin diseases.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.